GHSA-MX4J-WM6M-3MXR
Vulnerability from github – Published: 2025-10-09 12:30 – Updated: 2026-02-03 15:30
VLAI
Details
In the Linux kernel, the following vulnerability has been resolved:
wifi: mac80211: increase scan_ies_len for S1G
Currently the S1G capability element is not taken into account for the scan_ies_len, which leads to a buffer length validation failure in ieee80211_prep_hw_scan() and subsequent WARN in __ieee80211_start_scan(). This prevents hw scanning from functioning. To fix ensure we accommodate for the S1G capability length.
Severity
7.8 (High)
{
"affected": [],
"aliases": [
"CVE-2025-39957"
],
"database_specific": {
"cwe_ids": [],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2025-10-09T10:15:37Z",
"severity": "HIGH"
},
"details": "In the Linux kernel, the following vulnerability has been resolved:\n\nwifi: mac80211: increase scan_ies_len for S1G\n\nCurrently the S1G capability element is not taken into account\nfor the scan_ies_len, which leads to a buffer length validation\nfailure in ieee80211_prep_hw_scan() and subsequent WARN in\n__ieee80211_start_scan(). This prevents hw scanning from functioning.\nTo fix ensure we accommodate for the S1G capability length.",
"id": "GHSA-mx4j-wm6m-3mxr",
"modified": "2026-02-03T15:30:20Z",
"published": "2025-10-09T12:30:18Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-39957"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/0dbad5f5549e54ac269cc04ce89f212892a98cab"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/16c9244a62116fe148f6961753b68e7160799f97"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/32adb020b0c32939da1322dcc87fc0ae2bc935d1"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/7e2f3213e85eba00acb4cfe6d71647892d63c3a1"
},
{
"type": "WEB",
"url": "https://git.kernel.org/stable/c/93e063f15e17acb8cd6ac90c8f0802c2624e1a74"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
"type": "CVSS_V3"
}
]
}
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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